Title: Wind Energy Prediction System: a Review of Key Technologies

ABSTRACT

Wind energy is abundant and clean renewable source of energy. Due to the stochastic nature of the wind flows, wind energy is not a controllable energy resource that can be scheduled and planned in the same manner as conventional fossil energies. Therefore, reliable wind power prediction systems are required for managing the energy production from wind based sources upon the demand. In this article, we give a brief review on the composition of our proposed the energy management system and detailed review on wind power prediction technologies. There are three main components in our proposed system: wind power integration prediction technologies, 3D digital smart grid automatic construction platform and real-time energy monitoring platform.

Short Bio

Ling Wang is currently an associate professor in the department of computer science and Technology, Northeast Dianli University，China. She received the Ph.D degree in Computer Science from Chungbuk National University, Korea, in 2013. Her research interests are mainly in the areas of data mining, sensor networks, smart city, smart grid and new renewable energy. She is a number of IEEE，CCF and CSEE.

About Conference

FITAT is shaping up to be an annual conference to provide a platform for presentations and discussions of recent developments and future trends in Information Technology.

FITAT is emerging as a leading forum for IT professionals and researchers to discuss and present the latest research trends and results in the field of Information Technology (IT). FITAT 2016 promises to be exciting event that will host leading IT researchers from across the globe and will provide opportunity to build international research collaborations.